There’s a comfortable lie in B2B GTM: “CAC always goes up as you grow.”

Many teams accept it and build their entire growth strategy around it. The logic can sound tidy: your top channels saturate, new ones are less efficient, so CAC rises. This makes sense on the surface, so people  don’t question it. 

Great operators break from this script and ask the question everyone else avoids: “How do we grow while keeping CAC down?”

At ClickUp, in my role as the COO, I own all end-to-end business and revenue teams.  We cut CAC by over 50% while increasing our incremental ARR growth rate by over 80% in the last few years.  Our approach continues to work -  we have fast surpassed $300mn in ARR and continue only to accelerate growth 🚀.

How did we do it? We learnt from best practices in B2C, focused our culture on incrementality, made sense of our data (even when directional), and acted fast. Through this article, you will learn how to do this.

So if CAC doesn't have to rise, why does it keep rising for most companies? Five problems compound on each other.

Enter incrementality. As digital media was taking off, teams at Netflix and Uber pioneered incrementality, allowing them to deploy billions of dollars towards efficiently growing the business. 

These companies use Incrementality (causal impact measurement) to understand the true lift from their sales and marketing activities by comparing exposed groups to control groups, proving if their ads/activities truly cause a lift in sign-ups, not just correlate with them, but truly drive ROI. The goal here is to internalize that correlation ≠ causation, identify what is truly causal.

In some ways, these tests were inspired by medical trials - you only know if the drug is effective if you see true change in the experiment group (exposed to the drug) vs the control group (given a placebo). Modern growth teams applied these methods to measure causal impact, experiment, scale when it’s working, and stop investing when the incremental ROI starts to decline.

Another example, AirBnB famously slashed over $500mn from their performance marketing in 2020, and continued the trend in 2021. The story goes that someone accidentally turned off their branded Google search campaigns and they didn’t see sales decline - triggering a deeper inspection of every $$ they were spending and what was driving true ROI.

Now comes the million-dollar question - how do we apply this to B2B and more complex GTM orgs. There are no perfect answers, but a little effort and creativity can go far.
Here are five principles for applying incrementality to a complex revenue system with both PLG and SLG motions. 

As companies scale, complexity creeps in until your buyer experience resembles an “eight-layer cake". A single prospect might touch: SDR, AE, Sales Engineer, Service AE, Onboarding, CSM, Support, Professional Services, Value Engineer, Renewals…
ClickUp was guilty of this at one point. Many companies are. And it's important to admit that this isn't sophistication. It is bloat.

You can redesign your buying journey to be simple, high-ROI, and close to the metal. 

Begin simply by asking what’s truly needed vs good to have. Like AirBnB, try removing the good to have a layer with a group of customers/prospects. Most likely, you won’t see a huge decline in revenue.

Second, ask yourself can you consolidate roles? Specialize only when its really necessary. Simple is elegant, simple is beautiful

In performance marketing, PLG funnels, demand gen, top of funnel, you can measure true incremental ROI. You have enough volume and enough signal to isolate marginal ROI.

This is where geo-splits, audience-splits, spend elasticity tests, holdouts are feasible and work. A single rigorous top-of-funnel A/B test will tell you more about CAC efficiency than 20 attribution reports.

In sales motions, you rarely have the volume to run A/B test. But you are not looking for statistical purity, you need a directional signal to gauge what's worth acting on.

 A recent test we ran at ClickUp around lead routing and distribution:

The data wasn't perfect or sufficient to reach the gold standard statistical significance. But there was a directional insight: SDRs performed better with one segment, while AEs did better for another segment. This test informed our lead routing and how do we do maximize the yield from our inbound programs.

In most sales-led motions, a clean test design is very hard or not practical. You can’t “turn off” an AE for 10% of your customers to measure marginal bookings. But you can use directional models to approximate incrementality.

One path  is to simply look for nuggets of insight in your existing data. It won’t be perfect and you’ll need to find a way to separate correlation from causation, but you can extract meaningful clues. 

A ClickUp example: we were debating the long-term net value of attaching services to deals. When we look at past data of deals with vs without services, we  see a  25 point higher net retention for the services group on average.

But of course this is not bulletproof. Customers who buy services are already the ones that are more motivated to stay around longer and onboard more teams.

So then you can dive into your data further and try things like: find a point in time when you started offering services and look at a pre-post comparison. To make your argument very clear, try to isolate a firmographic or an ICP or a region where you know that during that time frame, this was the only major change made. Although not precisely perfect, you basically give it your best shot to isolate hints of where the incremental value is coming from.

My point here is that you can extract directional information from imperfect data - 

This is the new frontier of anything efficiency-related. Most companies used to default to “throw more bodies at the problem". Great operators in 2025 default to: "throw AI at the problem first". This allows us to keep CAC low.

At ClickUp, we have ClickUp Super Agents assisting our teams to do significantly more than what was ever thought possible. We use AI to augment our SEO and content generation efforts; our SDR productivity has 3xed because of AI tooling and personalization; we leverage agents to help us with deal execution and collaboration - pretty much all teams are using AI.  Impact: our headcount has grown by ~10% over last 3 years, while ARR is up ~400%

Companies that operate with an AI-first mindset will see the biggest incremental efficiency gains over the next decade.

This is the foundation on which all incrementality work rests. None of the above works without this cultural component in place.

Incrementality isn’t just a spreadsheet exercise. It’s an honesty exercise.

You cannot optimize a GTM machine if you aren't looking at each motion and asking plainly:

Is this driving incremental ROI or not?

True intellectual honesty means:

• Looking at facts objectively, regardless of whose idea they support

• Changing your position when evidence contradicts it

• Caring more about finding the truth than being right

Leaders who are intellectually honest, value truth-seeking over ego protection. When you establish this foundation, people stop playing games and start solving problems.

For many organizations, honest evaluation and decisive cutting alone can reduce CAC by 15–30% with no impact to growth -  however it needs a lot of courage and honesty to achieve this.

Efficient growth isn’t the result of any single tactic. It comes from running your business with a commitment to truth: simplifying where complexity adds no value, testing where signal is available, modeling where it isn’t, and defaulting to AI and automation before adding headcount.

When you operate this way, CAC comes down, growth accelerates, and your GTM engine becomes something you can scale with confidence instead of hope. 

One caveat: all of this only works if you have a product people actually want. Without that, CAC will rise no matter what you do. If your CAC keeps climbing despite doing everything right, that’s not a growth problem—it’s a product-market fit problem. You may have just learned something very real (and very expensive) about your offer.

But if you do have the product, here’s the truth: you can drive CAC down and accelerate growth—at the same time. The GTM leaders who question the status quo are the ones who build the next generation of category leaders.

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